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Prelint

Prevent product drift in AI-written code

Software Engineering
Developer Tools
Artificial Intelligence
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Hunted byRohan ChaubeyRohan Chaubey

AI writes your code at 10× speed. Prelint makes sure it's the right code - it reviews every PR against your ADRs, docs and past decisions, and catches product drift before it ships. On teams using several AI reviewers, ~40% of the issues fixed before merge are caught by Prelint.

Top comment

Hi Product Hunt, I’m Wojtek, one of the founders of Prelint.

Coding agents now produce more code than most teams can properly review. The obvious risk is bad code, but the more dangerous risk is good code that quietly builds the wrong product.

We saw this repeatedly in large production projects when we started using agents. A change would clear technical review, pass CI, yet still skip the transactional outbox pattern, introduce an unapproved dependency, change a permission rule or invent a business requirement. Nobody had made that decision, but it was now part of the product.

Prelint catches these decisions before they ship. It reads each change alongside your specifications, tickets and existing product context, then explains what the agent decided, what the consequences are and how difficult the choice will be to reverse. Your team can approve, correct or replace the decision, and Prelint carries that context into the next piece of work.

If you work with ADRs, our clients say it is the best tool they found for enforcing them with agents. On teams running Prelint alongside other AI reviewers, ~40% of the review comments that actually get fixed come from Prelint.

We started in GitHub and now support CLI and MCP, allowing agents to check product decisions while they work instead of waiting for a human to discover the problem at the end.

Prelint is not another technical code reviewer. These tell you whether the code works. Prelint tells you whether you should be building it.

If coding agents are contributing to your product, sign up at https://prelint.com, connect a GitHub repo and see what they've been deciding on your behalf. Then tell us what you like and what you'd love to see on top of it!

Use code: PH100 to get 100$ in additional free credits

Comment highlights

product drift is the real silent killer with ai code 👀 how do you keep false positves low?

The decision ledger is the right object, and it inherits the failure mode of every artifact that becomes authoritative: the entries nobody re-checks are the ones everybody trusts most. We hit the small version of this. A comment in our planner said the model was gpt-4o long after it had been switched to Haiku. Nothing broke, tests passed, the code was correct, and every human and every agent that read that file afterwards inherited a decision no one had made. The wrongness was invisible precisely because the artifact was doing its job. Weighting by authority makes this sharper rather than softer. The entries that most need an expiry are exactly the ones the weighting protects, and an agent reading your ledger will trust it more than it trusts the code, which is the correct behaviour right up until the entry is stale. So: does an entry ever get demoted, and what evidence demotes it? Ours are append-only, never deleted, because deleting a rule reopens the bug class it was written to prevent, so a retired entry leaves a tombstone pointing at the audit that killed it. The ledger records the deaths, not just the decisions.

"Good code that quietly builds the wrong product" is uncomfortably specific to something I have sitting in my own guidelines file right now: a component that fetches data directly instead of going through a hook, flagged months ago as a known violation, still not fixed because it passed review and works fine. That's the exact gap you're describing: nothing was broken, so nothing forced the conversation. Question: when Prelint flags a decision, does it also catch pre-existing drift already merged, or only new changes in the current PR?

Super interesting. I'm one person shipping with Claude Code daily. I had wrongly assumed drift was a coordination problem: several people, nobody reading each other's decisions. But what i found is that my own documented decisions go stale against my own code, and then they propagate.

Two from this month. A task in my tracker carried an explicit "do not do X without first verifying Y" warning. I wrote the checklist for that exact task without reading its notes, and caught it only when I went to close the task afterward. Separately, my canonical brand doc described a logo treatment that the actual shipped asset files contradicted. The doc was wrong for weeks and seeded the wrong version into an outgoing email template before I noticed.

Neither was an agent going rogue. Both were correct-looking work built on a confidently stated stale premise.

So my question: your supersession detection sounds aimed at documents contradicting each other. Does it handle a document contradicting the artifact it describes? The rotten context that actually cost me was doc versus reality, not doc versus doc, and the docs were the ones asserting loudest.

AI-generated code will only become more common, so governance tools like Prelint are going to be must-have!

Congrats Wojtek. Did you build this out of your own frustration or what inspired to think of solving this problem?

Congratulations. Does Prelint suggest the closest approved design pattern when it detects a violation?

When you build with AI, product consistency tends to erode gradually. Tools like Prelint can help stop that before it becomes expensive. Congrats on the launch.

the "decision ledger vs check code against docs" framing is what actually clicks for me. i keep a section in my own CLAUDE.md that's a manual, extremely low-tech version of this, not architecture notes, just "already tried this, here's why it didn't work" so the agent doesn't quietly rebuild the same mistake three months later. what i can't do by hand is catch the drift in real time instead of noticing the pattern repeating after the fact.

question on an existing repo: does the ledger backfill decisions from git history, or does it only start learning from the point you connect it?

Prelint is interesting because it seems to be focusing on the product intent. A lot of times AI can take its own direction, catching it soon from drifting by a tool is a great idea indeed!!

Being a SaaS founder, I love this idea. Preventing product drift feels just as important as preventing bugs. 👏

Congrats on the launch! I feel like the opposite is often the case where the ADR/docs etc are out of date and stale. How do you trust the materials it is basing the drift detection on?

When Prelint flags a conflict, can you jump straight to the exact source and version behind that decision? That would make it easier to tell a real conflict from stale context.

AI can generate code quickly, but making sure it stays aligned with product decisions is the harder problem. Probably the first product on PH which is tackling this issue.

The interesting bet here isn't catching bugs. It's catching code that works but quietly contradicts a decision the team made six months ago, and nobody has a linter for that. How much ADR discipline does a team need before Prelint has enough to check against?

About Prelint on Product Hunt

Prevent product drift in AI-written code

Prelint launched on Product Hunt on July 29th, 2026 and earned 588 upvotes and 128 comments, earning #1 Product of the Day. AI writes your code at 10× speed. Prelint makes sure it's the right code - it reviews every PR against your ADRs, docs and past decisions, and catches product drift before it ships. On teams using several AI reviewers, ~40% of the issues fixed before merge are caught by Prelint.

Prelint was featured in Software Engineering (42.8k followers), Developer Tools (517k followers) and Artificial Intelligence (475.2k followers) on Product Hunt. Together, these topics include over 196.8k products, making this a competitive space to launch in.

Who hunted Prelint?

Prelint was hunted by Rohan Chaubey. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

Reviews

Prelint has received 2 reviews on Product Hunt with an average rating of 5.00/5. Read all reviews on Product Hunt.

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